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8 min read • Sep 21, 2020
For the last few years, we have been talking about data in various superlatives and how it’s going to change our lives and the way we do business. As that idea is still present in 2020, it must mean that the trend is here to stay, and you can find the proof for it everywhere around you. Whether you buy suggested items on Amazon, or you see a relevant ad while surfing online, or you search for “Nearby” in Google Maps; there you go, you’ve just used a service that has data collection and advanced analytics included in its DNA.
The same thing is (fortunately) happening in the banking industry and other financial services are catching up too. Nowadays you might be living in a small, non-EU country and still have advanced mobile banking, access to online banks such as Revolut or N26 where you can set up account in 60 seconds, the ability to photograph your car accident and make a claim with your insurer, or to invest some money in stocks listed on the NASDAQ from the comfort of your couch as a small-scale retail investor. In 2020, whether you are a retail bank, investment bank, broker, exchange, wealth manager, insurer, fintech company or even a central bank or regulator, data has a huge impact on your business in several segments.
The segment most visible to end users can be referred to as customer intelligence. Gathering data from various data sources such as mobile banking apps, social media, GPS movements (if the customer agrees to this), and blending it into machine learning algorithms for smart segmentation can open ideas beyond pure demographics on how to best position your products, and how to position them at the right moment to the right segments of your customer portfolio.
Well-designed products in this area could really change the perspective of how young generations see banks and insurance companies. For example, I would love it if someone were to take and analyse data from my Garmin watch, and then could provide me with health insurance offers according to how active I am and would allow me to accept/sign up for these via my mobile banking app.
The second area of potential improvement is basically to reimagine business processes to boost efficiency in some business areas. This segment relies on data that companies already have, but are not using it in the right way or are not presenting it to the right people. For a sales rep to boost their performance, they need to have a few simple drill-down sheets on their BI tool on their mobile phone.
Forcing them to come to the office, export something and then create a pivot table out of it, does not boost performance. In all companies, all departments could make better use of the data they have with the right business intelligence tools, whether we speak of measuring call centre performance, boosting sales teams, or having a clear daily view of product profitability instead of a quarterly view.
Obviously, to support this broad number of use cases, companies have a wide range of technologies deployed. For the purpose of this blog, I will describe three different technology areas, corresponding to conclusions given by McKinsey, which we think will have a huge impact on how the financial industry is going to be doing business in the following years.
Data business and analytics in general is not an area where you can buy an out-of-the-box tool and solve your problems, it’s more of a platform approach where you enable various users by giving them the right data at the right moment. In large, heterogeneous organisations, this approach starts with the deployment of a modern and autonomous data warehouse and/or data lake, possibly by streaming data into a cloud. Appetites and needs in these large organisations can change quickly, and the only way you are able to answer those changing requirements on a daily basis is by quickly and proactively gathering data in a reusable repository while maintaining high data quality and data governance.
Looking from the perspective of the financial industry, this job becomes even more tricky because most (if not all) of them already have large sums of money invested in traditional DWH, OLAP cubes etc. which will require some redesigning in the following years. They will still remain here to serve some basic reporting or compliance reporting, but will not be able to tackle all the requirements that modern finance brings.
Leverage your data, discover where profit is being made, and effectively manage risk with automated business reporting for banks.
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